Search results for "probabilistic"
showing 10 items of 380 documents
Probabilistic inference of approximations
2006
We consider probabilistic inductive inference of Godel numbers of total recursive functions when the set of possible errors is allowed to be infinite, but with bounded density. We have obtained hierarchies of classes of functions identifiable with different probabilities up to sets with fixed density. The obtained hierarchies turn out to be different from those which we have in the case of exact identification.
Approximate Bayesian Computation for Forecasting in Hydrological models
2018
Approximate Bayesian Computation (ABC) is a statistical tool for handling parameter inference in a range of challenging statistical problems, mostly characterized by an intractable likelihood function. In this paper, we focus on the application of ABC to hydrological models, not as a tool for parametric inference, but as a mechanism for generating probabilistic forecasts. This mechanism is referred as Approximate Bayesian Forecasting (ABF). The abcd water balance model is applied to a case study on Aipe river basin in Columbia to demonstrate the applicability of ABF. The predictivity of the ABF is compared with the predictivity of the MCMC algorithm. The results show that the ABF method as …
The number of maximal subgroups and probabilistic generation of finite groups
2020
[EN] In this survey we present some significant bounds for the number of maximal subgroups of a given index of a finite group. As a consequence, new bounds for the number of random generators needed to generate a finite d-generated group with high probability which are significantly tighter than the ones obtained in the paper of Jaikin-Zapirain and Pyber (Random generation of finite and profinite groups and group enumeration, Ann. Math., 183 (2011) 769-814) are obtained. The results of Jaikin-Zapirain and Pyber, as well as other results of Lubotzky, Detomi, and Lucchini, appear as particular cases of our theorems.
TREEZZY2, a Fuzzy Logic Computer Code for Fault Tree and Event Tree Analyses
2004
In conventional approach to reliability analysis using logical trees methodologies, uncertainties in system components or basic events failure probabilities are approached by assuming probability distribution functions. However, data are often insufficient for statistical estimation, and therefore it is required to resort to approximate estimations. Moreover, complicate calculations are needed to propagate uncertainties up to the final results. In our work, in order to take account of the uncertainties in system failure probabilities, the methodology based on fuzzy sets theory is used both in fault tree and event tree analyses. This paper just presents our work in this issue, which resulted…
A probabilistic rainfall model to estimate the leading-edge lifetime of wind turbine blade coating system
2021
Rain-induced leading-edge erosion of wind turbine blades is associated with high repair and maintenance costs. For efficient operation and maintenance, erosion models are required that provide estimates of blade coating lifetime at a real scale. In this study, a statistical rainfall model is established that describes probabilistic distributions of rain parameters that are critical for site-specific leading-edge erosion assessment. A new droplet size distribution (DSD) is determined based on two years’ onshore rainfall data of an inland site in the Netherlands and the obtained DSD is compared with those from the literature. Joint probability distribution functions of rain intensities and dr…
Probabilistic classification of intracranial gliomas in digital microscope images based on EGFR quantity
2009
A glioma is a type of cancer occurring, in the majority of cases, in the brain. The World Health Organization (WHO) assigns a grade from I to IV to this tumor, with I being the least aggressive and IV being the most aggressive. In glioma cells of grade IV the Epidermal Growth Factor Receptors (EGFRs) are over expressed. In this paper we hypothesize that this overexpression occurs also for gliomas of grades I to III. Moreover, we present a medical study aiming to determine the correlation between the WHO classification and the EGFR quantity in glioma tissue. We define five quantity classes for EGFR. First, results of immunohistochemical staining on brain glioma slices, which visualize the EG…
Pelagic species identification by using a PNN neural network and echo-sounder data
2017
For several years, a group of CNR researchers conducted acoustic surveys in the Sicily Channel to estimate the biomass of small pelagic species, their geographical distribution and their variations over time. The instrument used to carry out these surveys is the scientific echo-sounder, set for different frequencies. The processing of the back scattered signals in the volume of water under investigation determines the abundance of the species. These data are then correlated with the biological data of experimental catches, to attribute the composition of the various fish schools investigated. Of course, the recognition of the fish schools helps to produce very good results, that is very clo…
Probabilistic foundations of contextuality
2017
Contextuality is usually defined as absence of a joint distribution for a set of measurements (random variables) with known joint distributions of some of its subsets. However, if these subsets of measurements are not disjoint, contextuality is mathematically impossible even if one generally allows (as one must) for random variables not to be jointly distributed. To avoid contradictions one has to adopt the Contextuality-by-Default approach: measurements made in different contexts are always distinct and stochastically unrelated to each other. Contextuality is reformulated then in terms of the (im)possibility of imposing on all the measurements in a system a joint distribution of a particul…
Hybrid coincidence and common fixed point theorems in Menger probabilistic metric spaces under a strict contractive condition with an application
2014
Abstract We prove some coincidence and common fixed point theorems for two hybrid pairs of mappings in Menger spaces satisfying a strict contractive condition. An illustrative example is given to support the genuineness of our extension besides deriving some related results. Then, we establish the corresponding common fixed point theorems in metric spaces. Finally, we utilize our main result to obtain the existence of a common solution for a system of Volterra type integral equations.
Strong Converse Results for Linking Operators and Convex Functions
2020
We consider a family B n , ρ c of operators which is a link between classical Baskakov operators (for ρ = ∞ ) and their genuine Durrmeyer type modification (for ρ = 1 ). First, we prove that for fixed n , c and a fixed convex function f , B n , ρ c f is decreasing with respect to ρ . We give two proofs, using various probabilistic considerations. Then, we combine this property with some existing direct and strong converse results for classical operators, in order to get such results for the operators B n , ρ c applied to convex functions.